It is widespread practice for the batteries of electric or hybrid vehicles HEV (Hybrid Electric Vehicles) to include a management system implementing an estimator of the state of charge SOC of the battery. The management system provides an operator or a driver of the vehicle with an estimation of an electrical charge remaining out of the capacity of the battery, for example presented in the form of operating battery life.
However, the operator or the pilot has more need of information concerning the energy available in the battery rather than information concerning its charge. In this regard, the state of energy SOE reflecting a percentage of energy remaining in the battery, is relevant information.
Currently, there is a limited number of estimators of the state of energy, SOE.
One drawback with some of the existing estimators is that they are limited in their use in as much as they are valid only in limited cases. For example, some estimators are valid only at the start of life because their estimation does not take account of the aging of the battery.
In their scientific publication A method for state of energy estimation of lithium-ion batteries based on neural network model, G. Dong et al. describe a method aimed at estimating the state of energy of batteries of lithium-ion type on the basis of a neural network model.
X. Liu et al. also describe, in A method for state of energy estimation of lithium-ion batteries at dynamic currents and temperatures, an estimator of the state of energy of neural network type.
One drawback with these estimators is that they are complex to implement.
The international patent application WO2016112960 describes a method for determining the state of energy SOE by integration of the curve of voltage at the terminals of the battery over a given state of charge SOC interval.
The patent application DE 10 2015 114652 A1, the patent application US2017/088072A1, and the scientific publication Maximum Available Capacity and Energy Estimation Based on Support Vector Machine Regression for Lithium-ion Battery by Zhongwei Deng et al., describe methods for determining the state of energy SOE of a battery.